Smart phones have come out with advanced features that can be useful for medical diagnosis. The Iphone X has a face recognition function to unlock the phone which could actually be used as a full functional 3D scanner. Unfortunately, only a few app developers have seen the potential of the Iphone X. The Bellus3D IOS app is dedicated for face scanning with the option to export data in slt/obj format for analysis on other software platforms. The face scans can be performed in 30 seconds including processing. A hardware adaption was developed to perform 3D scans also in the direction of backside of the Iphone X. To test the resolution and color representation of the Iphone X, scans were obtained of face phantoms and compared with high-end 3D scanners (Artec Spider/EVA and Vectra) using deviation maps. The Iphone X/Bellus3D performed best for the front view of the face. Presence of hair resulted in distortion of the side view. The mesh density was around 0.6-0.8 mm which is less compared to the Artec scanners (<0.2 mm) but similar to the Vectra. The photographic layover has a higher resolution (<0.2mm) and the 3D mesh enables to locate facial features with <0.5mm accuracy on different scans over time.
The Iphone X has potential to be used as a practical and relative low cost 3D scanner especially to provide absolute measurements of photographic facial features e.g. wrinkles, wounds, abnormalities for treatment/healing evaluation over time. The scans can be performed in a short time with real-time processing. App developers should become interested to develop dedicated apps for specific diagnostics and automated treatment evaluation.

Introduction: Management of skin cancer worldwide is often a challenge of scale, in that the resources available to detect and treat skin cancer are outweighed by the number of potential cases presented. This project aims to develop oneshot Stokes polarimetry using low-cost components to create a widely available skin cancer detection tool. Methods: A probe was developed to perform one-shot Stokes polarimetry on skin lesions in-vivo. Stokes polarimetry is an optical technique in which a laser of known polarization is fired at a target, and the altered polarization state of the returning light is measured. Typically, measuring a polarization state requires sequential measurements with four polarizing filters, however this probe contains four separate detectors to take these measurements in one shot. This probe was designed to perform at a lower cost and higher speed than traditional polarization methods. The Stokes vector is assessed as opposed to a Mueller matrix image to reduce the number of optical components and measurements required. The probe uses photodiodes and non-actuating film polarizing filters as detectors, and a partially-coherent laser diode as its illumination source. Results: Validation tests of each probe component, and the complete system put together, were performed to confirm the probe’s performance despite its low-cost components. This probe’s potential is demonstrated in a pilot clinical study on 69 skin lesions. The degree of polarization was found to be a factor by which melanoma could be potentially separated from other types of skin lesions.

Many point-of-care optical instruments use mass-produced, molded aspheric lenses to reduce the costs and complexity of portable microscopy and spectroscopy systems. This work explores a method for producing low-cost polymeric aspheres and assesses the lens quality for various material types. Single lens imaging of the US Air Force target was used to analyze the experimental resolution limit of each test case. An atomic force microscope was employed to determine the root-meansquare (RMS) surface roughness per lens. Initial results suggest that the system can generate lenses with equitable optical metrics, independent of material type. Preliminary resolution limits of the aspheres have achieved as low as 4 microns, for lenses spun at 250 rpms. Certain materials were found to be incompatible with the fabrication of plano-convex lenses due to the inability to de-mold after curing. Further improvements of the technique, specifically reduced resolution limits, would increase potential utility for low-cost applications in point-of-care optical systems.

There are two gaps in the present approach to breast cancer (BC) screening. First, access to mammography is often linked to socio-economic status, either of the individual or the country providing BC screening. Second, the BC incidence rate among women less than 40 years of age, commonly considered having high risk-benefit ratio for mammographic screening, is currently increasing the fastest of all age groups. Hence, both groups commonly access mammographic screening once they become symptomatic and thus are typically diagnosed with late-stage breast cancer, severely impacting long-term survival and often resulting in increased treatment costs. A safe and inexpensive pre-screening technology, which can identify women at risk of harboring early-stage BC or having very high mammographic breast density, and thus being at an elevated risk to develop BC in the future, can personalize a woman’s entry age into mammographic screening thus optimizing all women’s risk-benefit ratio related to their breast cancer screening. The Optical Breast Spectroscopy (OBS) device developed in our group is a portable device which quantifies the optical density of breast tissue employing up to 13 red/NIR wavelengths. Principal components analysis and tissue chromophore quantification allow identification of women with high mammographic density and hence elevated risk when combined with other risk factors such as BMI and menopausal status. Loss of left-right symmetry in the principal component scores or the tissue chromophores shows potential as an indicator of the presence of BC, although larger population studies are needed to validate the metrics. Longitudinal measurements improve the risk prediction.

Otitis media (OM) is a common ear infection and a leading cause of conductive hearing loss in the pediatric population. Current technologies can reasonably diagnose the infection with a sensitivity and specificity of 50–90% and 60–90%, respectively. However, these techniques provide limited information about the presence of biofilm or fluid formed behind the tympanic membrane (TM). Our group has developed handheld probes and portable optical coherence tomography (OCT) systems that have been used in various clinical studies to provide quantitative information about structural changes, and thus accurately characterize OM. Further, an automated machine learning-based approach from our group has been developed and integrated to classify OCT images associated with various stages of OM, without the need for interpretation by an expert reader.
In this study, we report a portable, low-cost, briefcase OCT system with automated classification for point-of-care diagnosis of OM. The briefcase OCT system cost < $8000USD with a 5-fold cost reduction and a 3-fold size reduction, compared to more standard OCT systems. Additionally, this system utilizes unique real-time mosaicking of surface video images that are synchronized with rapid A-scan acquisition, enabling computationally generated thickness maps and construction of cross-sectional B-mode images over extended lateral distances. Furthermore, a random-forest based classifier is utilized with an expanded feature set based on various statistics and metrics derived from OCT A-lines and B-scans. This system will help physicians and untrained users to collect OCT data and receive a diagnostic prediction indicating the presence and type of OM, potentially leading to more accurate point-of-care diagnoses.

Diffuse Optical Tomographic (DOT) experimental studies are performed in a dark environment, surrounded by dedicated instruments to acquire quality measurement data for the better image reconstruction. Hence, DOT experimental setups are bulky and educational experimental demonstration of DOT to the public in an open space is challenging. The International Year of Light (IYL 2015), motivated us to develop a DOT demonstration system to improve public understanding of the role of light in medical imaging. In this paper, we present a tabletop DOT system, that has four NIR light sources, six silicon-photodiode detectors, a control circuitry containing a 24-bit dual sigma-delta ADC with an ARM cortex-M3 processor and a MatLab based image reconstruction software. The control circuitry controls the light source and detector selections, measures diffused light and sends data to a laptop computer via USB for the low-resolution 2D DOT image reconstruction. The imaging domain was a tissue mimicking Intralipid and India ink solution in a circular tank, with a variable inhomogeneity location. We evaluated the system performance by demonstrating it on IISc Open Day an annual event opened for the general public in India. We performed interactive experimental demonstrations by allowing the audiences to place an optical inhomogeneity in the homogeneous phantom tank at their desired location. Our system was capable of localizing inhomogeneity in the reconstructed image from the experimental measurement data within a few seconds. The system was proven to be instrumental in demonstrating all of the basic principles and working principle of the DOT imaging in an interactive manner.

Cervical cancer is a leading cause of death for women in low resource settings. Visual methods for cervical cancer screening have become more widespread. To improve diagnosis of cervical precancerous lesions, a smartphone-based mobile colposcope was developed that uses auxiliary lens and light source inside a custom-designed case. However, acquiring a sharp image in a clinical setting using the mobile colposcope is tricky. For example, trying to use the phone’s auto-focus functionality struggles with the external lens placed in front of the phone’s internal lens, because translation of the internal lens has a non-trivial effect the image. Moreover, auto-focus algorithm struggles with the high contrast caused by artifacts as patients’ vaginal walls and pubic hair. A more robust algorithm that feeds commands back to the phone’s camera module is needed. Previously, a classifier that measures image sharpness was presented. Implementing a method to correct for an out of focus image requires manipulating the smartphone’s camera control parameters. This can be done either through the phone’s operating system (Camera 2 API) or through the manufacturer’s camera interface (Samsung Camera SDK), as called for from the application. This paper reviews how manipulations in a smartphone app affects image quality. In addition to image sharpness, analyses of brightness and color are also presented. Special apps that sweep through camera conditions were developed. Sample images from both anatomical models and calibration targets are given.

We report the development of a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user. It is composed of a cost-effective, portable microscope that can automatically auto-focus and scan over the size of an entire McMaster chamber (100 mm2) and capture high resolution (~1 µm) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. A convolutional neural network (CNN) automatically segments and analyzes the images to robustly separate eggs from background debris. The performance of the CNN is high despite the challenging, unbalanced nature of the images, where >95% of images contain no eggs and thus the potential for false-positives is high. Simple post-processing of the CNN output yields both egg species and egg counts. The system was validated by comparing hand counts with automated counts of samples containing eggs from ascarid, strongyle, and Trichuris nematodes, along with Eimeria oocysts. The system shows excellent performance, even on challenging Eimeria parasites whose small size is similar to fecal debris. The R2 values between hand and automated counts are >0.95 for both Eimeria and nematode parasites. Further, the diagnostic accuracy of our system for recommending antibiotic treatment is 100% for nematode parasites and 96% for Eimeria. As a further demonstration of utility, the system was used to conveniently quantify drug response over time, showing residual disease due to antibiotic resistance after 2 weeks.

We introduce a field-portable and cost-effective holographic imaging flow cytometer, which provides phase contrast microscopic images of the contents of water samples at a throughput of 100 ml/h. This imaging cytometer uses a high power multi-colored LED and a custom designed circuit to illuminate continuously flowing water samples with short-pulses of red, green, and blue light that are simultaneously on, thereby eliminating motion blur and making the system vibration resistant. The recorded color holograms are segmented and reconstructed in real time and are phase recovered using a deep learning-based algorithm. Weighing 1kg with the dimensions of 15.5 cm × 15 cm × 12.5 cm, our label-free imaging flow-cytometer is controlled by a laptop computer equipped with a graphical processing unit. We tested the capabilities of our field-portable device by imaging micro- and nano-plankton inside ocean water samples collected at six beaches along the California coastline. We also determined Pseudo-Nitzschia algae concentration of these samples, providing a good agreement with the measurements made by the California Department of Public Health. Our device represents 1-2 orders of magnitude reduction in the cost and size of an imaging flow cytometer compared to state-of-the-art designs, while providing a similar or better performance in terms of volumetric throughput, detection limit and imaging resolution.

Recent advances in inkjet-printed optics have created a new class of lens fabrication technique. Dubbed DotLens, a single of which weighs less than 50 mg and occupies a volume less than 50 μL. DotLens can be attached onto any smartphone camera akin to a contact lens, and turn the smartphones into a microscope. In this paper, we show recent results from images collected from a variety of biological samples. Lately, we have demonstrated that by data analytics the smartphone microscope is capable of detect nanoscale objects and their minute color changes, called nanocolorimetry. We have applied it to the detection and quantification of lean ion in drinking water with performance surpassing the EPA standard.

Digital holographic microscopy (DHM) has various unique advantages, such as large depth-of-field, simplicity of the optical setup, and the capability to reconstruct both the amplitude and phase images of samples. However, due to the use of narrow-band illumination sources, holographic imaging of pathology samples is limited by imperfect color representation, which might negatively impact diagnostic decisions. Here, an accurate-color holographic microscopy framework is presented using absorbance spectrum estimation of histochemical stains with a minimum mean square error (MMSE) criterion. Using this method, a pathology slide is imaged using a holographic microscope at a small number of wavelengths (e.g., three to six). These multispectral images are then used to estimate the absorbance spectrum of the sample at each pixel location, and to calculate a color-corrected tristimulus image. Based on this approach, we further optimize the selection of wavelengths by minimizing the color error of the reconstructed image compared to the ground truth, color-accurate image that is obtained using 31 illumination wavelengths (acquired sequentially). Based on this absorbance spectrum estimation method and the selection of optimal illumination wavelengths, we significantly improved the average color error of holographic images of 25 samples with different tissue-stain combinations, including breast, kidney, esophagus, lung, liver, artery, and Pap smear samples combined with H&E, PAS, MT, EVG, Congo Red, GMS, Alcian Blue, Jones, Gram, and Pap stains. The presented method provides a practical guide for accurate-color holographic imaging of stained tissue samples and cells for digital pathology and telemedicine applications.

Background: When running large trials, histopathology services are used to assess the state of a tissue. However, in many clinics in low resource settings there are large variations in quality of such services, specifically in biopsy processing and histopathological interpretation/assessment of images. Quality assurance (QA) is needed, but it involves physically mailing slides to a remote clinic. A telemedicine solution can address this challenge. Methods: A novel smartphone adapter for microscopes was developed, consisting of a 3D printed attachment and software integration for the image capture. The attachment is used to couple the eyepiece of a low end microscope to a smartphone (Samsung J530). Image capture was controlled through the EVA System app. The entire system was characterized optically using standard calibration targets. Additionally, images captured on the attachment were compared to the standard method of shipping and scanning slides in a high end slice scanner at a remote clinic. Results: The resolution of the entire system (microscope + phone) with a 40X objective was <1 μm. The system is currently undergoing testing in Nigeria as part of a broader cervical cancer screening study.1 Preliminary testing showed similar image quality between the smartphone-based system and high end scanner. Whole slide imaging requires stitching together images into a mosaic, made possible by a mobile application. Conclusion: The results here show that coupling a low end microscope to a smartphone yields similar results to a transporting slides to a high end microscope. Such an attachment can thus potentially provide a telemedicine solution to researchers in low resource settings.

Anemia affects more than ¼ of the world’s population, mostly concentrated in low-resource areas, and carries serious health risks. Yet current screening methods are inadequate due to their inability to separate iron deficiency anemia (IDA) from genetic anemias such as thalassemia trait (TT), thus preventing targeted supplementation of oral iron. Here we present a cost-effective and accurate approach to diagnose anemia and anemia type using measures of cell morphology determined through machine learning applied to optical light scattering measurements. A partial least squares model shows that our system can accurately extract mean cell volume, red cell size heterogeneity, and mean cell hemoglobin concentration with high accuracy. These clinical parameters (or the raw data itself) can be submitted to machine learning algorithms such as quadratic discriminants or support vector machines to classify a patient into healthy, IDA, or TT. A clinical trial conducted on over 268 Chinese children, of which 49 had IDA and 24 had TT, shows >98% sensitivity and specificity for diagnosing anemia, with 81% sensitivity and 86% specificity for discriminating IDA and TT. The majority of the misdiagnoses are IDA patients with particularly severe anemia, possibly requring hospital care. Therefore, in a screening paradigm where anyone testing positive for TT is sent to the hospital for gold-standard diagnosis and care, we maximize patient benefit while minimizing use of scarce resources.

The diffusion of miniaturized analysis platforms has spurred the development of portable and compact imaging systems. We present a compact, lens-based imaging module that implements wavefront division off-axis holography on a commercial microfluidic chip, thanks to the insertion of a diffraction grating. The initial architecture is realized in three configurations. Different positioning of the grating respect to the microfluidic channel (parallel and orthogonal) are explored, and an enhancement of the imaging system compactness and price-effectiveness is realized by further functionalizing the chip with micro-optics. The three configurations are separately analyzed and tested. It is demonstrated that the characteristic features of Digital Holography, i.e. label-free imaging, quantitative phase mapping and flexible refocusing, are preserved, and differences and specific fields of applicability are highlighted.

Diabetic foot ulcers are common, recurrent, leading frequently to foot amputation and even death. Their management requires early expert infection assessment and remains a major challenge for the clinicians. Assessment also necessitates culture-sensitivity of the swab taken from ulcer (the gold-standard technique) to identify the bacteria colonizing the infected wound. The process requires accurate swabbing, culturing in a BSL-2 facility and takes anywhere between 2-5 days leading to prescription of generic antibiotics by the doctors. Regular swabbing is a cumbersome procedure to understand and regularly follow up on the microflora population.
Each bacteria has characteristic emission fluorescence when excited with different wavelength of light sources. A novel device, developed by us, leverages this auto-fluorescence property enabling us to develop a multispectral imaging platform. The device captures the spectral signatures of metabolic growth markers along with markers released when a microbiome causes infection to detect and assess the bacterial gram type.
A preliminary clinical study was conducted at MV Hospital for Diabetes and Prof M Viswanathan Diabetes Research Centre, Chennai. Of the 50 patients imaged, the spectral signatures obtained from our device was able to find significant differences between gram positive and gram-negative bacteria. The device spectral results was compared against deep tissue culture biopsy and the device was able to detect gram positives and gram negatives with 83% and 81% accuracy respectively. The device also picked up 7 polymicrobial sites.
In summary, the device can be used as an important tool in guided swabbing, assessment of a wound and understanding its microbiome pattern. The device helps to differentiate infected from non infected wounds, classifies the infected ones broadly according to their gram type and enables real time follow up of wounds. In future, fluorescence spectral signatures will be obtained using more excitation wavelengths to differentiate the exact species of bacteria and to improve on the accuracy of classification to enable treatment protocols using tailored antibiotics.

Light-Assisted Drying (LAD) is a novel biopreservation technique which allows proteins to be immobilized in a dry, amorphous solid at room temperature. Indicator proteins are used in a variety of diagnostic assays ranging from highthroughput 96-well plates to new microfluidic devices. A challenge in the development of protein-based assays is preserving the structure of the protein during production and storage of the assay, as the structure of the protein is responsible for its functional activity. Freeze-drying or freezing are currently the standard for the preservation of proteins, but these methods are expensive and can be challenging in some environments due to a lack of available infrastructure. An inexpensive, simple processing method that enables supra-zero temperature storage of proteins used in assays is needed. Light-assisted drying offers a relatively inexpensive method for drying samples. Proteins suspended in a trehalose solution are dehydrated using near-infrared laser light. The laser radiation speeds drying and as water is removed the sugar forms a protective matrix. In this set of studies we investigate the effect varying protein concentration and protein size on EMC. We also test the functionality of a model protein, lysozyme, after LAD processing compared to air drying, samples incubated at a temperature comparable to LAD, and a control solution kept at 8°C.

Direct detection of genetic biomarkers in tissue and body fluids without complex target extraction and amplification processes can revolutionize nucleic acid-based diagnostics by enabling the use of this technology at the point-of-care. The development of point-of-care diagnostics is important to increase access to early treatment in underserved populations in low to middle income countries, which are disproportionally affected by infectious diseases and increasingly affected by certain types of cancer. The main obstacle to the development of such technologies is the low concentration of target sequences that makes this goal challenging. We report a method for direct detection of pathogen RNA in blood lysate using a bioassay using surface-enhanced Raman spectroscopy (SERS)-based detection assay that can be integrated in a “lab-in-a-stick” portable device. We could directly detect synthetic target with a limit of detection of 200 fM and, more importantly, we detected P. falciparum malaria parasite RNA directly in infected red blood cells lysate. Additionally, this paper will discuss the use of the developed assay for the identification of head and neck squamous cell carcinoma (HNSCC), which is an increasingly prevalent malignancy in low to middle income countries.

Advances in consumer electronics and affordable high functioning optics have led to renewed interest in the development and application of portable microscopes for the remote diagnosis of diseases such as malaria. Indeed, better tools for malaria diagnosis are necessary to combat increasing rates of false-negative diagnosis and drug resistance. In this work, the capabilities and utility of a portable, multimodal microscopy system designed for malaria diagnosis are explored. The system, which combines off-the-shelf optical components with a Raspberry Pi for data collection and a microfluidic cartridge for sample preparation, is capable of capturing brightfield, fluorescent, and cross-polarized images of thin blood smears. Parameters for each imaging modality are defined and related to their potential diagnostic utility. Samples of Plasmodium falciparum cultures were stained either with fluorophores or with a dual Giemsa-fluorophore procedure and examined using the portable and gold-standard microscopes. Preliminary results indicate that the microscope is capable of nearly diffraction limited performance and can distinguish rings, trophozoites, and schizonts in fluorescence and brightfield modes along with hemozoin crystals in cross-polarized mode. Parasitemia measurements for simulated mixed-stage, severe infections show strong agreement with Giemsa-stained gold-standard measurements. If cost and durability limitations can be overcome, this microscopy system may be able to augment malaria-screening rapid diagnostic tests to enable the more precise distribution of antimalarial medications at the point-of-care.

A multi-spectral imaging system was built from low cost components: LEDs and an area-scan camera, that are all housed within a case and controlled by a tablet computer. The system can capture images of tissue at 14 different wavelengths in <10 seconds. Spectra derived from different lateral positions in the images were then fit to a theoretical model based on GPU Monte Carlo simulations in order to estimate the scattering and absorption properties of the tissue at different layers. To better characterize the system’s ability to measure changes in tissue oxy- and deoxyhemoglobin content, images of the forearm of healthy volunteers were imaged before, during, and after short term ischemia and then reperfusion of the arm, which lowered the amount of oxyhemoglobin in the tissue. To decrease tissue oxygen saturation, blood flow to the arm was restricted for 120 sec using a sphygmomanometer (blood pressure cuff), with pressure levels of 170 mm Hg. Repeated measurements were captured with the arm held in a special mount with an aperture built to fix the tissue in place. Overall, the before, during, and after spectra, where there are notable differences between oxy and deoxy-hemoglobin. The analyses showed a significant decrease in oxygen saturation of the venous plexus layer, with moderate changes in blood content. However, changes in the error function were much more sensitive to blood content than oxygen saturation. These results suggest that changes in oxygen saturation levels can be measured using a low cost setup, although at lower accuracy relative to blood content.

Smartphone based wound image analysis approach has been recently developed to capture high resolution digital images of the wound and determine the wound size via image segmentation algorithms. Smartphone based technology has also been developed to obtain spectroscopic information at discrete point locations for brain imaging applications. Herein, we developed a low-cost smartphone based near-infrared (NIR) imaging device (between 650-1000 nm) that can measure tissue oxygenation in order to analyze wound healing status. Oxygen supply to ulcers is a key limiting factor for successful healing, and hence changes in tissue oxygenation are a precursor to visual changes in the wound. The use of multi-wavelength near-infrared light allows subcutaneous mapping of oxy- and deoxy-hemoglobin changes (or in turn tissue oxygenation changes). Validation studies were performed in controls to demonstrate changes in oxygenation (from diffuse reflectance changes) in response to venous occlusion. Currently, studies on diabetic foot ulcers is carried out using the cell phone-based imaging tool to obtain sub-surface tissue oxygenation maps of the wound and its surrounding. Smartphone based assessment of wounds will assist clinicians and nurses in any clinical in-house setting including low resource settings. In future, patients with chronic wounds can also actively participate (and comply) in their treatment process.

According to the WHO, 15,000 children under five years are dying every day from preventable causes with 80% of these children being born in low-income countries. Portable optical medical diagnostic devices can help physicians, nurses and untrained health workers to objectively identify children who are at a higher risk of dying. In the last 2 years, we collected the oxygenation values of the brachioradialis muscle, using a commercial Near Infrared Spectroscopy (NIRS) device, in 200 children under 5 years admitted in two hospitals in Uganda. Data revealed that the tissue oxygen saturation decrease during a vascular occlusion predicts children at higher risk better than other vital signs (SpO2, respiration rate, heart rate and temperature). Based on these results, we designed a low cost Continuous Wave Spatially Resolved NIRS device controlled by a smartphone in order to extend our study to a larger population and confirm our observation. The total cost of this device (excluding the smartphone) is less than $100. The preliminary tests suggest a significant potential of our low cost mobile NIRS device and oxygenation values closely matching those reported by the best device on the market.

The mobile health field has given rise to a surge of point-of-care diagnostic attachments for mobile phones. These attachments, however, are limited in adoption in low-resource settings due to initial acquisition and subsequent maintenance cost challenges. Point-of-care devices that require no or minimum attachment can make a great impact to the accessibility of such devices in resource-poor regions. In this abstract, we report a simulation study to demonstrate the feasibility of using an ultra-low-cost color-paper filter and a mobile phone to perform broadband pulse oximetry. We run a series of GPU-based Monte Carlo simulations using a previously segmented 7T MRI scan of a finger 3D model. We sweep the optical properties of the finger tissues between the wavelengh band of 400-800 nm with a 1 nm increment, with intensity based on the measured spectrum of an iPhone 8’s LED. We also measured the transmission spectra from paper filters of various colors, which we used to further alter the light source spectrum. Using a discretized photoplethysmogram (PPG) signal, we simulate a 60 bpm oscillation optical measurements due to an up to 15% volume changes of the finger arterioles. Simulations were repeated for various peripheral blood oxygen levels (SpO2). Finally, we estimate the SpO2 using the simulated PPG signals using the Ratio of Ratios (RR) method. We evaluate the performance of different color paper filters by comparing 1) total optical signal intensity, 2) maximum magnitude of the RR signal variations and 3) the correlation of the computed and assumed SpO2 values. We found that the purple-colored filter produced the highest RR signal variations and the cyan-colored paper resulted in the largest SpO2 changes in the tested range.

Optical spectroscopic devices have historically been too expensive or not portable enough to take full advantage of their abilities to offer real-time, on-site, objective results, especially in the developing world. Recent advancements toward smaller and cheaper hardware, especially in the visible and near infrared (NIR) ranges, could enable widespread use in low resource settings, down to a rural health clinic or at the individual farm level. We recently designed and tested a spectroscopic device with these goals in mind. It is based on an initial commercial version of a low cost MEMS spectral detection chip operating in the NIR, or more properly short wave infrared (SWIR) region. Custom optics, electronics, and mechanical designs were created to produce a complete handheld system capable of operation in the lab or in the field. Initial lab testing indicated excellent reproducibility both within and between five different devices. We have verified desired performance (e.g. acceptable signal to noise for target integration times, spectral features equivalent to lab-grade devices, etc.) for applications including pharmaceutical analysis and for analyzing multiple agricultural materials, including soils, plants, fertilizers, and manures. We have also developed a custom mobile app to accompany the devices in upcoming field testing, which will validate their performance in realistic settings in sub-Saharan Africa.

Oral cavity cancers are the fourth common cancers in companion dogs. Common malignant oral tumors in pet dogs include squamous cell carcinoma, melanoma and fibrosarcoma while benign tumors include epulids, papilomas and extramedullary plasmacytomas. Malignant tumors are often aggressive with potential to invade locally and distantly. The occurrence of malignant and benign lesions are evenly matched. Hence early diagnosis is important for management. Current diagnosis is based on aspiration cytology and biopsy, which is a time consuming and invasive procedure. Hence less invasive, reliable and quicker diagnostic technique is preferable. Raman spectroscopy-based studies have demonstrated the feasibility of classifying normal, premalignant and malignant oral conditions in human subjects as well as rodent animal models. The present study was undertaken to explore feasibility of classifying canine tumour and normal oral tissues with Raman spectroscopy (RS). RS is a non-destructive vibrational spectroscopic technique, which provides information about molecular composition, molecular structures and molecular interactions in tissue. Raman spectra of histopathologically confirmed 13 (10-abnormal and 3- normal) samples were acquired using a Raman Confocal Microscope (Raman alpha300R, WITEC, GMBH, GERMANY). Spectral acquisition parameters were : laser power-28mW, integration-10 s and averaged over 10 accumulations. Spectra were pre-processed and subjected to unsupervised Principal-Component Analysis (PCA) to identify trends of classification. Supervised LDA (Linear-Discriminant Analysis) showed high classification efficiency. Findings of this explorative study suggest that Raman spectroscopy can be developed as a non-invasive, label free, early diagnostic tool for cancers in pet dog.

The use of modern medical equipment in crisis and war zones for emergency medical teams (EMT) of the World Health Organization is an important factor for fast and efficient humanitarian aid. A reliable vital parameter monitoring is fundamental in mobile hospitals. Currently, the maintenance of medical devices in structurally weak areas is difficult due to the company’s proprietary standards. Rough environmental influences such as dust, moisture, heat or shocks can lead to dysfunktion and long-lasting failure of instrumentation. Pulse oximetry and blood pressure measurements are particularly susceptible. We developed an open source vital parameter monitoring system for use under adverse conditions and structurally weak areas. Blood oxygen levels, heart rate, blood pressure and electrocardiograms are recorded and transferred to decentralized displays. The main focus is on reliability and robustness of various optical sensors for pulse oximetry, the repair capability of the system also for non-technical personnel and the availability of individual standard components. Therefore we implemented a monitoring system basing on individual microcontrollers for each vital parameter. Different optical sensors for measurement in transmission and reflection were tested at suitable body sites with near-surface arteries. In combination with the electrocardiogram, evaluation of the pulse transit time enables continuous blood pressure measurements. A specially developed optical reflective sensor allows reliable measurement of blood oxygen level. For extended blood pressure measurements, the pulsetransit-time method (PTT) was implemented and enables a continuous monitoring. Even in emergencies, the trend in blood pressure can be monitored with PTT without prior calibration. The reliability was investigated.

We report an application of the smartphone as an accurate and unbiased reading platform of lateral flow assay. In particular, this report focuses on detection of food-borne bacteria from samples extracted from various food matrices. Lateral flow assay is widely accepted methodology due to its on-site result and low-cost analysis even though sensitivity is not as good as standard laboratory equipment. Antibody-antigen relationship is translated into a color change on the nitrocellulose pad and interpretation of this color change causes obscurity, particularly around the detection limit of the assay. Based on its integrated camera and computing power, we provide an objective and accurate method to determine the bacterial cell concentration from the food matrix based on the regression model based on the bacterial concentration and RGB channel color changes. 3-D printed sample holder was designed for one of the representative commercial lateral flow assay and in-house application was developed in Android studio that solves the inverse problem instantly to provide cell concentration to the user.